class_docstr: The default implementation of `DdpAccelerator`, which is just a thin wrapper
  around PyTorch's `DistributedDataParallel`.
code: def _remove_torch_ddp_prefix(
      module: torch.nn.Module,
      state_dict: StateDictType,
      prefix: str,
      *args: Any,
  ) -> None:
      for key in list(state_dict.keys()):
          if not key.startswith(prefix + "module."):
              continue
          new_key = key.replace(prefix + "module.", "", 1)
          state_dict[new_key] = state_dict[key]
          del state_dict[key]
  
imports: import os
  from typing import Union, Tuple, OrderedDict, Dict, NamedTuple, List, Optional, Any, Sequence, TYPE_CHECKING
  import torch
  import torch.distributed
  from torch.cuda import amp
  from torch.nn.utils import clip_grad_norm_
  from allennlp.common import Registrable
  from allennlp.common.util import int_to_device
  from allennlp.nn.parallel.sharded_module_mixin import ShardedModuleMixin
label_desc: Use image node_id 4 for calling the TorchDdpAccelerator obj's underlying member method code with example usage: obj._remove_torch_ddp_prefix(module, state_dict, prefix) without return types